bert-japanese-finetuned-Ukraine-tweet

This model is a fine-tuned version of cl-tohoku/bert-base-japanese-whole-word-masking on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.1318
• Accuracy: 0.5280
• F1: 0.4447

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
1.3734	1.0	21	1.2022	0.5248	0.4394
1.1804	2.0	42	1.1680	0.5155	0.4284
1.1396	3.0	63	1.1318	0.5280	0.4447

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.12.0
• Tokenizers 0.13.3